G. Raso

65 papers receiving 914 citations

Peers

G. Raso
Comparison fields: 5 of 98
  • Radiation 252
  • Radiology, Nuclear Medicine and Imaging 276
  • Computer Vision and Pattern Recognition 167
  • Media Technology 69
  • Artificial Intelligence 250
Replace Liyuan Chen with:
Liyuan Chen China
F. Fauci Italy
David A. Reimann United States
Bernd Gutmann Germany
Hiroshi Tsutsui Japan
Jovan G. Brankov United States
Dong Zeng China
Zhanli Hu China
Cheng‐Bin Jin China
Stephen Pistorius Canada
G. Raso relative to Liyuan Chen China Liyuan Chen's profile →
Citations per field
00.5×3.3×
Liyuan Chen · 1×
Citations per year

Countries citing papers authored by G. Raso

Since Specialization
Citations

This map shows the geographic impact of G. Raso's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by G. Raso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Raso more than expected).

Fields of papers citing papers by G. Raso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. Raso. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by G. Raso. The network helps show where G. Raso may publish in the future.

Co-authors

The 25 scholars most cited alongside G. Raso, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with G. Raso Line = papers co-authored together G. Raso links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012116
2 200688
3 201645
4 200634
5 200734
6 201029
7 201427
8 201027
9 200627
10 200626
11 201725
12 200925
13 201724
14 201922
15 201221
16 201621
17 202020
18 199620
19 201918
20 200916

About G. Raso

G. Raso is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Radiation, having authored 70 papers that have together received 956 indexed citations. Recurring topics across this work include AI in cancer detection (22 papers), Advanced X-ray and CT Imaging (20 papers), Advanced Semiconductor Detectors and Materials (20 papers), Radiation Detection and Scintillator Technologies (12 papers), Digital Radiography and Breast Imaging (9 papers), Systemic Lupus Erythematosus Research (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Medical Imaging Techniques and Applications (6 papers). The work is most often cited by research in Radiation (252 citations), Radiology, Nuclear Medicine and Imaging (276 citations), Computer Vision and Pattern Recognition (167 citations), Media Technology (69 citations) and Artificial Intelligence (250 citations). G. Raso has collaborated with scholars based in Italy, Cuba and United Kingdom. Frequent co-authors include Donato Cascio, F. Fauci, L. Abbene, G. Gerardi, R. Magro, F. Principato, S. Del Sordo, S. Stumbo, Andrea Zappettini and Manuele Bettelli. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Applied Sciences, Sensors, Medical Physics and Pattern Recognition Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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